GPR Signature Detection and Decomposition for Mapping Buried Utilities with Complex Spatial Configuration
Publication: Journal of Computing in Civil Engineering
Volume 32, Issue 4
Abstract
The information of exact locations of underground utilities is an essential piece of evidence for preventing utility strikes in excavation work. Ground penetrating radar (GPR), which has emerged as a promising, nondestructive solution for this purpose, is capable of capturing radar reflections that are then recorded as GPR scans. To determine the location, dimension, size, and spatial configuration of pipes, radargrams must be further interpreted to extract the shapes (e.g., hyperbolas and lines) and to identify the feature components (e.g., hyperbola apex, rising and trailing segment, and junctions of intersecting hyperbolas). This paper introduces a new drop–flow algorithm that automates the detection and decomposition of GPR signatures into feature components in two-dimensional scans. Commencing at a strip of pixels from the top of the edge of the scan image, the algorithm mimics the motion of a raindrop falling or flowing as it touches the edge pixels of the image. The movement of the raindrop completes the decomposition of the GPR signature when it touches the ground (i.e., the bottom of the edge image). This new algorithm was tested using both synthetic and field data. The promising results indicate the drop–flow algorithm’s ability to segment the intersecting hyperbolas and to identify the feature components of each hyperbola, forming the basis for estimating the spatial configuration, size, and location of underground pipes.
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Acknowledgments
This research was partially funded by the National Science Foundation (NSF) via Grant CMMI-1462638. The authors gratefully acknowledge NSF’s support. Any opinions, findings, and conclusions in this paper are those of the authors and do not necessarily reflect the views of NSF or Purdue University.
References
Al-Nuaimy, W., Y. Huang, M. Nakhkash, M. Fang, V. Nguyen, and A. Eriksen. 2000. “Automatic detection of buried utilities and solid objects with GPR using neural networks and pattern recognition.” J. Appl. Geophys. 43 (2): 157–165. https://doi.org/10.1016/S0926-9851(99)00055-5.
Annan, A. 1999. Practical processing of GPR data. Mississauga, ON, Canada: Sensors and Software.
Annan, A., and S. Cosway 1992. “Ground penetrating radar survey design.” In Proc., 4th Annual Symp. on Applications of Geophysics to Engineering and Environmental Problems, 329–351. Denver: EEGS.
Benedetto, A., and L. Pajewski 2015. Civil engineering applications of ground penetrating radar. New York: Springer.
Besaw, L. E., and P. J. Stimac. 2015. “Deep convolutional neural networks for classifying GPR B-scans.” In Proc., SPIE Defense and Security on Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX. Washington, DC: SPIE.
Boniger, U., and J. Tronicke. 2012. “Subsurface utility extraction and characterization: Combining GPR symmetry and polarization attributes.” IEEE Trans. Geosci. Remote Sens. 50 (3): 736–746. https://doi.org/10.1109/TGRS.2011.2163413.
Borgioli, G., L. Capineri, P. Falorni, S. Matucci, and C. G. Windsor. 2008. “The detection of buried pipes from time-of-flight radar data.” IEEE Trans. Geosci. Remote Sens. 46 (8): 2254–2266. https://doi.org/10.1109/TGRS.2008.917211.
Chaudhuri, B. B., and G. Samanta. 1991. “Elliptic fit of objects in two and three dimensions by moment of inertia optimization.” Pattern Recognit. Lett. 12 (1): 1–7. https://doi.org/10.1016/0167-8655(91)90021-D.
Chen, H., and A. G. Cohn 2010. “Probabilistic robust hyperbola mixture model for interpreting ground penetrating radar data.” In Proc., 2010 Int. Joint Conf. on Neural Networks (IJCNN), 1–8. New York: IEEE.
Congedo, G., G. Dimauro, S. Impedovo, and G. Pirlo. 1995. “Segmentation of numeric strings.” In Proc., 3rd Int. Conf. on Document Analysis and Recognition, 1038–1041. New York: IEEE.
Daniels, D. J. 2004. Ground penetrating radar. Stevenage, UK: IET.
Dasgupta, A., and A. E. Raftery. 1998. “Detecting features in spatial point processes with clutter via model-based clustering.” J. Am. Stat. Assoc. 93 (441): 294–302. https://doi.org/10.1080/01621459.1998.10474110.
Delbo, S., P. Gamba, and D. Roccato. 2000. “A fuzzy shell clustering approach to recognize hyperbolic signatures in subsurface radar images.” IEEE Trans. Geosci. Remote Sens. 38 (3): 1447–1451. https://doi.org/10.1109/36.843039.
El-Mahallawy, M. S., and M. Hashim. 2013. “Material classification of underground utilities from GPR images using DCT-based SVM approach.” IEEE Geosci. Remote Sens. Lett. 10 (6): 1542–1546. https://doi.org/10.1109/LGRS.2013.2261796.
Feng, K., J. Zhao, J. Wu, and S. Ge 2014. “Cross-correlation attribute analysis of GPR data for tunnel engineering.” In Proc., 15th Int. Conf. on Ground Penetrating Radar, 435–440. New York: IEEE.
Fitzgibbon, A., M. Pilu, and R. B. Fisher. 1999. “Direct least square fitting of ellipses.” IEEE Trans. Pattern Anal. Mach. Intell. 21 (5): 476–480. https://doi.org/10.1109/34.765658.
Frigui, H., and P. Gader. 2009. “Detection and discrimination of land mines in ground-penetrating radar based on edge histogram descriptors and a possibilistic k-nearest neighbor classifier.” IEEE Trans. Fuzzy Syst. 17 (1): 185–199. https://doi.org/10.1109/TFUZZ.2008.2005249.
Geoscanners. 2017. “GPRSoft.” Accessed January 10, 2017. http://www.geoscanners.com/gprsoft.htm.
Gerlitz, K., M. D. Knoll, G. M. Cross, R. D. Luzitano, and R. Knight. 1993. “Processing ground penetrating radar data to improve resolution of near-surface targets.” In Proc., 6th EEGS Symp. on the Application of Geophysics to Engineering and Environmental Problems, 561–574. Denver: EEGS.
Giannopoulos, A. 2005. “Modelling ground penetrating radar by GprMax.” Constr. Build. Mater. 19 (10): 755–762. https://doi.org/10.1016/j.conbuildmat.2005.06.007.
Goodman, D. 2017. “GPR-slice.” Accessed January 10, 2017. http://www.gpr-survey.com/.
GPR Professional Services Incorporated. 2017. “Ground penetrating radar: Storage tank (UST) & drum locating.” Accessed November 4, 2017. http://www.gprps.com/gpr-services/storage-tank-and-drum-locating/.
GSSI (Geophysical Survey Systems, Inc.). 2017. “UtilityScan Pro, industry standard in GPR for utility mapping and locating: Data examples.” Accessed November 4, 2017. http://www.geophysical.com/utilityscanpro.htm.
Hugenschmidt, J. 2000. “Railway track inspection using GPR.” J. Appl. Geophys. 43 (2–4): 147–155.
Hugenschmidt, J. 2002. “Concrete bridge inspection with a mobile GPR system.” Constr. Build. Mater. 16 (3): 147–154.
Janning, R., T. Horváth, A. Busche, and L. Schmidt-Thieme. 2012. “GamRec: A clustering method using geometrical background knowledge for GPR data preprocessing.” In Artificial intelligence applications and innovations, 347–356. New York: Springer.
Jaw, S. W., and M. Hashim. 2013. “Locational accuracy of underground utility mapping using ground penetrating radar.” Tunnelling Underground Space Technol. 35 (1): 20–29. https://doi.org/10.1016/j.tust.2012.11.007.
Kida, H., O. Iwaki, and K. Kawada. 1986. “Document recognition system for office automation.” In Proc., 8th ICPR, 446–448. New York: IAPR.
Kim, J.-H., S.-J. Cho, and M.-J. Yi. 2007. “Removal of ringing noise in GPR data by signal processing.” Geosci. J. 11 (1): 75–81. https://doi.org/10.1007/BF02910382.
Lehmann, F., and A. G. Green. 2000. “Topographic migration of georadar data: Implications for acquisition and processing.” Geophysics 65 (3): 836–848. https://doi.org/10.1190/1.1444781.
Lehmann, F., H. Horstmeyer, A. Green, J. Sexton, and M. Coulibaly. 1996. “Georadar data from the northern Sahara desert: Problems and processing strategies.” In Proc., 6th Int. Conf. on Ground Penetrating Radar, 51–56. New York: IEEE.
Lester, J., and L. E. Bernold. 2007. “Innovative process to characterize buried utilities using ground penetrating radar.” Autom. Constr. 16 (4): 546–555. https://doi.org/10.1016/j.autcon.2006.09.004.
Leuschen, C., and R. Plumb. 2000. “A matched-filter approach to wave migration.” J. Appl. Geophys. 43 (2): 271–280. https://doi.org/10.1016/S0926-9851(99)00064-6.
Li, S., H. Cai, D. M. Abraham, and P. Mao. 2014. “Estimating features of underground utilities: Hybrid GPR/GPS approach.” J. Comput. Civ. Eng. 30 (1): 04014108. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000443.
Maas, C., and J. Schmalzl. 2013. “Using pattern recognition to automatically localize reflection hyperbolas in data from ground penetrating radar.” Comput. Geosci. 58 (1): 116–125. https://doi.org/10.1016/j.cageo.2013.04.012.
Malagodi, S., L. Orlando, and S. Piro. 1996. “Approaches to increase resolution of radar signal.” In Proc., 6th Int. Conf. on Ground Penetrating Radar, 283–288. New York: IEEE.
Mast, J. E., and E. M. Johansson. 1994. Three-dimensional ground penetrating radar imaging using multi-frequency diffraction tomography. Livermore, CA: Lawrence Livermore National Laboratory.
Meer, P., and B. Georgescu. 2001. “Edge detection with embedded confidence.” IEEE Trans. Pattern Anal. Mach. Intell. 23 (12): 1351–1365. https://doi.org/10.1109/34.977560.
Mertens, L., R. Persico, L. Matera, and S. Lambot. 2016. “Automated detection of reflection hyperbolas in complex GPR images with no a priori knowledge on the medium.” IEEE Trans. Geosci. Remote Sens. 54 (1): 580–596. https://doi.org/10.1109/TGRS.2015.2462727.
Metje, N., B. Ahmad, and S. M. Crossland. 2015. “Causes, impacts, and costs of strikes on buried utility assets.” Proc. Inst. Civ. Eng. Munic. Eng. 168 (3): 165–174. https://doi.org/10.1680/jmuen.14.00035.
Moysey, S., R. J. Knight, and H. M. Jol. 2006. “Texture-based classification of ground-penetrating radar images.” Geophys. 71 (6): K111–K118. https://doi.org/10.1190/1.2356114.
Ni, S. H., Y. H. Huang, K. F. Lo, and D. C. Lin. 2010. “Buried pipe detection by ground penetrating radar using the discrete wavelet transform.” Comput. Geotech. 37 (4): 440–448. https://doi.org/10.1016/j.compgeo.2010.01.003.
Olhoeft, G. R. 2000. “Maximizing the information return from ground penetrating radar.” J. Appl. Geophys. 43 (2): 175–187. https://doi.org/10.1016/S0926-9851(99)00057-9.
Otsu, N. 1979. “A threshold selection method from gray-level histograms.” IEEE Trans. Syst. Man Cybern. 9 (1): 62–66. https://doi.org/10.1109/TSMC.1979.4310076.
PHMSA (Pipeline and Hazardous Materials Safety Administration). 2017. “Significant incident 20-year trend.” Accessed June 1, 2017. https://www.phmsa.dot.gov/pipeline/library/data-stats/pipelineincidenttrends.
Radar Solutions International Incorporated. 2017. “RSI—case study #5 utility mapping at a liquid natural gas facility in northeastern Massachusetts.” Accessed November 4, 2017. http://www.radar-solutions.com/CaseStudies/CaseStudy5.html.
Roackaway, T., and J. A. Rivard. 2010. “Application of ground penetrating radar in the urban environment.” In Proc., 13th Int. Conf. on Ground Penetrating Radar (GPR), 1–4. New York: IEEE.
Sandmeier Geophysical Research. 2017. “Reflexw.” Accessed January 10, 2017. http://www.sandmeier-geo.de/reflexw.html.
Sato, M., K. Takahashi, and L. Yi. 2014. “Optimization of data sampling and image reconstruction by GPR.” In Proc., 15th Int. Conf. Ground Penetrating Radar (GPR). New York: IEEE.
Sensor & Software Incorporated. 2017a. “GPR for golf green management.” Accessed November 4, 2017. https://www.sensoft.ca/case-studies/golf-green-management/.
Sensor & Software Incorporated. 2017b. “GPR for mapping multiple utilities.” Accessed November 4, 2017. https://www.sensoft.ca/case-studies/locating-pipes-cables_subsurface-utility-mapping/.
Sensor & Software Incorporated. 2017c. “Subsurface utility engineering for water installation.” Accessed November 4, 2017. https://www.sensoft.ca/case-studies/subsurface-utility-engineering-water-installation/.
Sham, J. F., and W. Lai. 2015. “A new algorithm for more accurate estimation of wave propagation velocity by common-offset survey method.” In Proc., Int. Symp. on Non-Destructive Testing in Civil Engineering, 305–315. Amsterdam, Netherlands: Elsevier.
Shihab, S., and W. Al-Nuaimy. 2005. “Radius estimation for cylindrical objects detected by ground penetrating radar.” Subsurface Sens. Technol. Appl. 6 (2): 151–166. https://doi.org/10.1007/s11220-005-0004-1.
Talmaki, S., and V. R. Kamat. 2014. “Real-time hybrid virtuality for prevention of excavation related utility strikes.” J. Comput. Civ. Eng. 28 (3): 04014001. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000269.
Tillard, S., and J. C. Dubois. 1992. “Influence of lithology on radar echoes: Analysis with respect to electromagnetic parameters and rock anisotropy.” In Proc., 4th Int. Conf. on Ground Penetrating Radar. New York: IEEE.
Tillard, S., and J. C. Dubois. 1995. “Analysis of GPR data: Wave propagation velocity determination.” J. Appl. Geophys. 33 (1–3): 77–91. https://doi.org/10.1016/0926-9851(95)90031-4.
Torrione, P., K. Morton Jr., and L. E. Besaw. 2011. “Sensor fusion approaches for EMI and GPR-based subsurface threat identification.” In Vol. 8017 of Proc., SPIE Defense and Security on Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI, 2001–2015. Washington, DC: SPIE.
Wang, T., and M. L. Oristaglio. 2000. “GPR imaging using the generalized Radon transform.” Geophysics 65 (5): 1553–1559. https://doi.org/10.1190/1.1444843.
Warren, C., A. Giannopoulos, and I. Giannakis. 2016. “gprMax: Open source software to simulate electromagnetic wave propagation for ground penetrating radar.” Comput. Phys. Commun. 209 (1): 163–170. https://doi.org/10.1016/j.cpc.2016.08.020.
Wilson, J. N., P. D. Gader, and H. J. Suh. 2005. “Compactometry, the density distribution, and their use in discriminating landmines and clutter.” In Vol. 5794 of Proc., SPIE Defense and Security on Detection and Sensing of Mines, Explosive Objects, and Obscured Targets X, 1132–1140. Washington, DC: SPIE.
Windsor, C., L. Capineri, P. Falorni, S. Matucci, and G. Borgioli. 2005. “The estimation of buried pipe diameters using ground penetrating radar.” Insight-Non-Destr. Test. Condition Monit. 47 (7): 394–399. https://doi.org/10.1784/insi.2005.47.7.394.
Xu, D., and Y. Tian. 2015. “A comprehensive survey of clustering algorithms.” Ann. Data Sci. 2 (2): 165–193. https://doi.org/10.1007/s40745-015-0040-1.
Yungang, Z., and Z. Changshui. 2003. “A new algorithm for character segmentation of license plate.” In Proc., IEEE IV2003 Intelligent Vehicles Symp., 106–109. New York: IEEE.
Žalik, K. R., and B. Žalik. 2009. “A sweep-line algorithm for spatial clustering.” Adv. Eng. Software 40 (6): 445–451. https://doi.org/10.1016/j.advengsoft.2008.06.003.
Zanzi, L., and D. Arosio 2013. “Sensitivity and accuracy in rebar diameter measurements from dual-polarized GPR data.” Constr. Build. Mater. 48 (1): 1293–1301. https://doi.org/10.1016/j.conbuildmat.2013.05.009.
Zhang, Z. 1997. “Parameter estimation techniques: A tutorial with application to conic fitting.” Image Vision Comput. 15 (1): 59–76. https://doi.org/10.1016/S0262-8856(96)01112-2.
Zoidis, N., E. Tatsis, C. Vlachopoulos, and A. Gotzamanis, and J. S. Clausen, and D. G. Aggelis, and T. E. Matikas 2013. “Inspection, evaluation and repair monitoring of cracked concrete floor using NDT methods.” Constr. Build. Mater. 48 (1): 1302–1308. https://doi.org/10.1016/j.conbuildmat.2013.05.009.
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Journal of Computing in Civil Engineering
Volume 32 • Issue 4 • July 2018
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©2018 American Society of Civil Engineers.
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Received: Jun 21, 2017
Accepted: Nov 9, 2017
Published online: May 9, 2018
Published in print: Jul 1, 2018
Discussion open until: Oct 9, 2018
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